A unified framework for multi-fiber tractography using the unscented Kalman Filter
Speaker: Yogesh Rathi , Harvard Medical School/BWH
Date: April 1 2010
Time: 3:00PM to 4:00PM
Location: 32-D507
Host: Polina Golland, CSAIL
Contact: Polina Golland, x38005, polina@csail.mit.edu
Relevant URL: In this talk I will present a unified framework for joint fiber model
estimation and tractography. Existing techniques estimate the local
fiber orientation at each voxel independently so there is no running
knowledge of confidence in the measured signal or estimated fiber
orientation. In this work, fiber tracking is formulated as recursive
estimation: at each step of tracing the fiber, the current estimate of
the signal is guided by the previous. Thus, the inherent correlation
in diffusion of water along the fiber path is taken into account
during model estimation. To this end, we will employ the unscented
Kalman filter (UKF). The proposed framework has several advantages:
1). Can be used with both parametric and non-parametric models.
2). Confidence in the estimated model is obtained as a by-product.
I will also briefly describe the application of the tractography
results to statistical analysis and classification of first-episode
schizophrenia patients.
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